Project Overview
To provide CMS data expertise and conduct quick-turnaround analyses and longer-term research studies using this data to explore a range of disability and aging policy topics of interest to the Administration for Community Living.
The Administration for Community Living needs timely access to data and analyses for program monitoring and strategic planning. The agency sought to engage a partner with deep CMS data expertise to explore health care trends and needs among its priority populations, including older adults and people with disabilities.
Mission Analytics Group
U.S. Department of Health and Human Services, Administration for Community Living
Mathematica supports ACL by providing access to and analyzing CMS data to explore critical research questions about ACL focus populations. Mathematica’s Health Data Innovation Lab enables our team to access a wide range of CMS data, including Medicare and Medicaid claims and enrollment files and nursing home assessments. Drawing on deep knowledge of this data, including our experience producing the research-ready Medicaid T-MSIS (Transformed Medicaid Statistical Information System) Analytic Files, Mathematica acquires, links, and prepares CMS data files for analysis. We also link CMS data to informative non-CMS sources, such as the Area Health Resource Files for geographic analyses of health care use and the Centers for Disease Control and Prevention’s Social Vulnerability Index for exploring disparities in care.
Using this data, Mathematica conducts ongoing quick-turnaround analyses and longer-term studies on topics of interest to ACL, such as the impacts of COVID-19 impacts on care delivery (including forgone care), long-term care service use, home and community-based service use, geographic variation in care access, and demographics and disease prevalence among Medicare and Medicaid populations.
For each study we design, we provide code and specifications to ACL that can be easily replicated and updated over time as CMS data is updated, allowing for rapid turnaround of subsequent analyses as the most up-to-date data becomes available.
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